For each type of bet I calculated the average amount put in, and assumed the actual bets are distributed uniformly from 0 to twice the average.

I don't know how important this is, but I doubt that's at all close to the actual distribution. I would expect tiny bets to be the vast majority of bets placed. I suspect that there are thousands of sub-1 BTC bets, and very few larger bets.

I will make a text file available detailing all the bets processed in the last couple of weeks, so that you can make a proper analysis.

But first I have to go light some fires and let a little dog out to pee.

It is indeed important. If we assume the extreme that all bets are either 0 or the max bet, the variance increases 100-fold which means that the result is only about 1.2 sd below the mean. A list of bets can resolve this particular issue.

Honestly it looks like its in the realm of possibility to me. Compare it to the 11/08 jump.

That's what I think too. I did those calculations in an attempt to demonstrate that this is indeed nothing to worry about (not the best way to do science, but my methodology was simple enough not to be influenced by my prejudice). Which is why I was a bit surprised by my result, but variance in the bet amounts may explain them away.

It is indeed important. If we assume the extreme that all bets are either 0 or the max bet, the variance increases 100-fold which means that the result is only about 1.2 sd below the mean. A list of bets can resolve this particular issue.

It is indeed important. If we assume the extreme that all bets are either 0 or the max bet, the variance increases 100-fold which means that the result is only about 1.2 sd below the mean. A list of bets can resolve this particular issue.

It is indeed important. If we assume the extreme that all bets are either 0 or the max bet, the variance increases 100-fold which means that the result is only about 1.2 sd below the mean. A list of bets can resolve this particular issue.

What fields do you want to see per bet?

block number, date, bet type, stake, result, return?

Anything else?

These should be enough.

OK, I made a text file of the bets from the last 1500 blocks or so (since the decline started) here (both the same, the 2nd is gzip compressed)

Ok. We have a total of 79,000 bets resulting in a total profit of -5121 BTC. If we assume the bets are fixed and their results are variable, then the mean profit is 1285 BTC and the variance is 3084000 BTC^2. This means the result is 3.65 sd below the mean.

The probability for a normal random variable to be this low is 0.000132. We need to correct for selection bias; there may be better ways to do it but multiplying by 1000 would be the right ballpark (the effective number of choices for the period to investigate). This means that there would be about 13% chance of getting results this bad somewhere on the graph. This means they indeed have some bad luck, but not so much so to indicate something may be wrong.

Ok. We have a total of 79,000 bets resulting in a total profit of -5121 BTC. If we assume the bets are fixed and their results are variable, then the mean profit is 1285 BTC and the variance is 3084000 BTC^2. This means the result is 3.65 sd below the mean.

The probability for a normal random variable to be this low is 0.000132. We need to correct for selection bias; there may be better ways to do it but multiplying by 1000 would be the right ballpark (the effective number of choices for the period to investigate). This means that there would be about 13% chance of getting results this bad somewhere on the graph. This means they indeed have some bad luck, but not so much so to indicate something may be wrong.

It just occurred to me that not all the bets are independent events. You can't tell from the data I provided, but it's possible to place multiple bets within a single transaction. All such bets get the same 'magic number'.

I don't know what impact that would have on your calculations. If you like, I could add a txid to each bet so you can tell which are grouped with which.

Ok. We have a total of 79,000 bets resulting in a total profit of -5121 BTC. If we assume the bets are fixed and their results are variable, then the mean profit is 1285 BTC and the variance is 3084000 BTC^2. This means the result is 3.65 sd below the mean.

The probability for a normal random variable to be this low is 0.000132. We need to correct for selection bias; there may be better ways to do it but multiplying by 1000 would be the right ballpark (the effective number of choices for the period to investigate). This means that there would be about 13% chance of getting results this bad somewhere on the graph. This means they indeed have some bad luck, but not so much so to indicate something may be wrong.

It just occurred to me that not all the bets are independent events. You can't tell from the data I provided, but it's possible to place multiple bets within a single transaction. All such bets get the same 'magic number'.

I don't know what impact that would have on your calculations. If you like, I could add a txid to each bet so you can tell which are grouped with which.

It would be a bit more work to take into account grouped bets. But the impact of the fact that those exist is that the variance will be higher, meaning the results are even more plausible.

I think it would be fine to try to carry out a more sophisticated statistical test, and/or ask the operators if they know of anything which could cause a problem. But if not that's also fine, the results are within the realm of possibility.

Ok. We have a total of 79,000 bets resulting in a total profit of -5121 BTC. If we assume the bets are fixed and their results are variable, then the mean profit is 1285 BTC and the variance is 3084000 BTC^2. This means the result is 3.65 sd below the mean.

The probability for a normal random variable to be this low is 0.000132. We need to correct for selection bias; there may be better ways to do it but multiplying by 1000 would be the right ballpark (the effective number of choices for the period to investigate). This means that there would be about 13% chance of getting results this bad somewhere on the graph. This means they indeed have some bad luck, but not so much so to indicate something may be wrong.

1000 seems too big to me.

there have been 1.5m bets in total so 20 seems more reasonable than 1000.

Ok. We have a total of 79,000 bets resulting in a total profit of -5121 BTC. If we assume the bets are fixed and their results are variable, then the mean profit is 1285 BTC and the variance is 3084000 BTC^2. This means the result is 3.65 sd below the mean.

The probability for a normal random variable to be this low is 0.000132. We need to correct for selection bias; there may be better ways to do it but multiplying by 1000 would be the right ballpark (the effective number of choices for the period to investigate). This means that there would be about 13% chance of getting results this bad somewhere on the graph. This means they indeed have some bad luck, but not so much so to indicate something may be wrong.

1000 seems too big to me.

there have been 1.5m bets in total so 20 seems more reasonable than 1000.

This has very little to do with the number of bets (in particular you seem to want to use the base-2 log but I see no justification for that. Probabilities are not on the same scale as information bits). It's about how many choices there are to choose the period to analyze. With a very simplistic calculation, you have 180 choices for the start date and about 10 choices for the length, which would come up as 1800. Now you have to correct for the correlations, the fact that we didn't actually go and optimize the worst period, etc. Maybe something like 500 or even less is more appropriate but again this is just a back-of-the-envelope calculation. I agree that it is unusual enough to look into it further.

Doesn't this reversal make it even more suspicious? I mean that steep rise is equally unexpected like the steep loss before. What is the probability of these two events happening directly one after the other?